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A novel wake-up receiver for wireless sensor networks is introduced. It operates with a modified medium access protocol (MAC), allowing low-energy consumption and practical latency. The ultra-low-power wake-up receiver operates with enhanced duty-cycled listening. The analysis of energy models of the duty-cycle-based communication is presented. All...
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The Internet of Things (IoT) is revolutionizing technology in a wide variety of areas, from smart healthcare to smart transportation. Due to the increasing trend in the number of IoT devices and their different levels of energy requirements, one of the significant concerns in IoT implementations is powering up the IoT devices with conventional limi...
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... The WuRx must be operated duty-cycled to ensure a low average energy consumption. Recent works introducing an LNA are [2,3]. Fig. 1 shows the common building blocks of different hardware architectures in the state of the art (SoA). ...
... To minimize energy consumption modern receivers are typically duty cycled [9]- [17], i.e., they listen only at predetermined time periods, and sleep otherwise. To alert the receiver of an incoming message, the transmitter sends a preamble either at the beginning of a listening period (e.g., [9], [17]- [19]), or immediately in which case the preamble is long enough to cover at least one listening period (e.g., [12], [15]). In both cases (as seen in [9], [12], [15], [17]- [19]) the receiver performs a binary hypothesis test, referred to as channel sensing, during the listening periods, to decide whether or not a preamble is present. ...
... To alert the receiver of an incoming message, the transmitter sends a preamble either at the beginning of a listening period (e.g., [9], [17]- [19]), or immediately in which case the preamble is long enough to cover at least one listening period (e.g., [12], [15]). In both cases (as seen in [9], [12], [15], [17]- [19]) the receiver performs a binary hypothesis test, referred to as channel sensing, during the listening periods, to decide whether or not a preamble is present. ...
This paper proposes an energy-efficient detection scheme, referred to as AdaSense, that is particularly suitable in the sparse regime when events to be detected happen rarely. To minimize energy consumption, AdaSense exploits the dependency between the receiver noise figure (i.e., the receiver added noise) and the receiver power consumption; less noisy channel observations typically imply higher power consumption. AdaSense is duty-cycled and begins each cycle with a few channel observations in a low-power-low-reliability mode. Based on these observations, it makes a first tentative decision on whether or not a message is present. If no message is declared, AdaSense waits till the beginning of the next cycle and starts afresh. If a message is tentatively declared, AdaSense enters a confirmation second phase, takes more samples, but now in a high-power-high-reliability mode. If these observations confirm the tentative decision, AdaSense stops, else AdaSense waits till the beginning of the next cycle and starts afresh in the low-power-low-reliability mode. Compared to prominent detection schemes such as the clear channel assessment algorithm of the Berkeley Media Access Control (BMAC) protocol, AdaSense provides relative energy gains that grow unbounded in the small probability of false-alarm regime, as communication gets sparser. In the non-asymptotic regime, energy gains are 30% to 75% for communication scenarios typically found in the context of wake-up receivers.
... On the other hand, in [13], the authors proposed a wakeup receiver based on a tuned RF architecture that requires filtering for selectivity and high RF gain for high sensitivity. This architecture fits better due to its simplicity and low cost of implementation; it consists of an LNA to amplify the received signal with minimal noise, an envelope detector to downconvert the RF signal to a baseband with a significantly lower frequency than that of the carrier, a baseband amplifier to boost the voltage level of the extracted envelope, a hysteresis comparator, and a decoder. ...
Wireless communication integration is related to many challenges such as reliability, quality of service, communication range, and energy consumption. As the overall performance of wireless sensor networks (WSN) will be improved if the capacity of each sensor node is optimized, several techniques are used to fine-tune the various circuits of each node. In recent works, the wake-up receiver nodes have been introduced to minimize latencies without increasing energy consumption. To overcome the sensitivity of wake-up receiver limitations, a design of a low-noise amplifier (LNA) with several design specifications is required. This article discusses the relevance of the wake-up receiver in WSN applications and provides a brief study of this component. An LNA design for WSN wake-up receiver applications is presented. The challenging task of the LNA design is to provide equitable trade-off performances such as noise figure, gain, power consumption, impedance matching, and linearity. The LNA circuit is designed for wireless personal area network (WLAN) standards utilizing RF-TSMC CMOS 0.18 μm. Two innovative techniques are applied to the LNA topology to improve its performance: forward body biasing is used to reduce power consumption by 11.43 mW, and substrate resistance is added to reduce noise by 1.8 dB. The developed LNA achieves a noise figure of 1.6 dB and a power gain of 21.7 dB at 5.2 GHz. At 0.6 V, the designed LNA dissipates 0.87 mW.
... The WuRx's sensitivity is limited due to the noise level of the passive diode detector circuit. Overcoming this limit, the implementation of [BDK18a] added a dutycycled low-noise amplifier (LNA) resulting in a sensitivity of −90 dBm. During active phase, the power consumption reaches over 1 mW. ...
... Operational amplifiers (OAs) are used as voltage amplifiers in implementations like [BDK18b; FSD21; Kaz+21]. [BDK18a] introduces a voltage amplifier with two bipolar junction transistors (BJTs). ...
For power-limited wireless sensor networks, energy efficiency is a critical concern. Receiving packages is proven to be one of the most power-consuming tasks in a WSN. To address this problem, the asynchronous communication is based on wake-up receivers. The proposed receiver circuit can detect on-off keying pulses inside the 868 MHz band with a sensitivity of -60 dBm. The power consumption of the circuit is only 3.6 µW. The circuit design is kept simple, only requiring commercial off-the-shelf components like general-purpose operational amplifiers and comparators.
... A sensitivity of −71 dBm was achieved. The LNA-based design from [BDK18] utilizes bipolar junction transistor (BJT)based LNA and LF amplifier. The LNA amplifies 36 dB while only consuming 550 µA. ...
... The average power consumption is 3 µW while sensitivity is −90 dBm. Further improving the implementation of [BDK18], regarding average power consumption and sensitivity, is not the goal of this publication. Because of the utilization of a custom BJT-based LNAs, working in the sub-milliampere range, experimental results are very hard to reproduce. ...
... COTS LNAs are used in our proposed circuit, at the cost of a gain reduction and higher current demand. Further problems within the communication scheme of [BDK18] were detected, leading inevitably to a random packet loss. This publication introduces a special lowfrequency modulation and measurements were made to ensure no random packet loss occurs. ...
For power-limited wireless sensor networks, energy efficiency is a critical concern. Receiving packets is proven to be one of the most power-consuming tasks of a wireless sensor node. Wake-up receivers enable asynchronous communication while maintaining low power consumption. Recent wake-up receiver designs have low sensitivity, high power consumption, or lack of reliability and reproducibility. The proposed receiver circuit utilizes a two-stage low-noise amplifier to achieve a sensitivity of −80 dBm. A duty-cycling approach was introduced to reduce the average power consumption to 14.2 µW. The reliability of the proposed design was ensured by introducing a special low-frequency modulation scheme. The reproducibility of the design was ensured by only using commercial off-the-shelf components.
... On the other hand, this affects the latency, reliability, and current consumption of the system. The authors in [30] used a two-stage LNA based on bipolar junction transistors (BJTs) and achieved a sensitivity of −90 dBm. However, the presented architecture means a higher circuitry effort due to numerous passive components. ...
... Table 1 summarizes the mentioned properties of the approaches from the SoA. Figure 2 shows an overview of the described WuRx architectures based on their power consumption, sensitivity, carrier frequency, and LF amplifiers. It can be seen that WuRx with RF amplifiers [29,30] achieves sensitivity better than −70 dBm with a power consumption of 8 µW. However, the integration of the LNA increases the average current consumption and the latency of the system compared to an always-on listening approach. ...
With the introduction of Internet of Things (IoT) technology in several sectors, wireless, reliable, and energy-saving communication in distributed sensor networks are more important than ever. Thereby, wake-up technologies are becoming increasingly important as they significantly contribute to reducing the energy consumption of wireless sensor nodes. In an indoor environment, the use of wireless sensors, in general, is more challenging due to signal fading and reflections and needs, therefore, to be critically investigated. This paper discusses the performance analysis of wake-up receiver (WuRx) architectures based on two low frequency (LF) amplifier approaches with regard to sensitivity, power consumption, and package error rate (PER). Factors that affect systems were compared and analyzed by analytical modeling, simulation results, and experimental studies with both architectures. The developed WuRx operates in the 868 MHz band using on-off-keying (OOK) signals while supporting address detection to wake up only the targeted network node. By using an indoor setup, the signal strength and PER of received signal strength indicator (RSSI) in different rooms and distances were determined to build a wireless sensor network. The results show a wake-up packets (WuPts) detection probability of about 90% for an interior distance of up to 34 m.
... To perform this task, the WuRs are composed of an RF front-end and a digital baseband back-end, with a pattern recognizer or signal correlator used to identify the wake-up identifier. Power savings introduced by using WuRs are mostly observed in low-activity and low-average throughput applications, as the main radio interface is in sleep mode during a significant amount of time [4]. Due to its inherent simplicity, the on-off keying (OOK) modulation scheme is frequently the preferred option when designing a WuR. ...
... A common solution to improve the WuR's sensitivity consists of placing an LNA before the envelope detector to boost the signal-to-noise ratio (SNR), this architecture is known as tuned RF (TRF). A high gain is required from the LNA to reduce the contribution of the noise figure (NF) of the envelope detector, leading to a tradeoff between sensitivity and power dissipation [4]. To improve the circuit's interference resilience, high-Q off-chip components can be used to implement the input filter [13]. ...
... to a trade-off between sensitivity and power dissipation [4]. To improve the circuit's interference resilience, high-Q off-chip components can be used to implement the input filter [13]. ...
Wireless sensor network (WSN) applications are under extensive research and development due to the need to interconnect devices with each other. To reduce latency while keeping very low power consumption, the implementation of a wake-up receiver (WuR) is of particular interest. In WuR implementations, meeting high performance metrics is a design challenge, and the obtention of high-sensitivity, high data rate, low-power-consumption WuRs is not a straightforward procedure. The focus of our proposals is centered on power consumption and area reduction to provide high integrability and maintain a low cost-per-node, while we simultaneously improve circuit sensitivity. Firstly, we present a two-stage design based on a feedback technique and improve the area use, power consumption and sensitivity of the circuit by adding a current-reuse approach. The first solution is composed of a feedback amplifier, two op-amps plus a low-pass filter. The circuit achieves a sensitivity of –63.2 dBm with a power consumption of 6.77 µA and an area as low as 398 × 266 µm2. With the current-reuse feedback amplifier, the power consumption is halved in the second circuit (resulting in 3.63 µA), and the resulting circuit area is as low as 262 × 262 µm2. Thanks to the nature of the circuit, the sensitivity is improved to –75 dBm. This latter proposal is particularly suitable in applications where a fully integrated WuR is desired, providing a reasonable sensitivity with a low power consumption and a very low die footprint, therefore facilitating integration with other components of the WSN node. A thorough discussion of the most relevant state-of-the-art solutions is presented, too, and the two developed solutions are compared to the most relevant contributions available in the literature.
... Nevertheless, recent developments have revealed exciting possibilities to enhan energy harvesting (EH) efficiency by designing suitable converters, combining converte in hybrid solutions, and adopting opportunities for wireless energy transmissio Developments in microelectronics enable significant energy savings, making an ener supply from ambient sources increasingly practicable. Wake-up receivers swit unnecessary system parts entirely off and reduce energy consumption during sleepi phases [4,5]. Data aggregation techniques [1], clustering, and intelligent routing realiz significant energy savings on the network level. ...
Advanced sensors are becoming essential for modern factories, as they contribute by gathering comprehensive data about machines, processes, and human-machine interaction. They play an important role in improving manufacturing performance, in-factory logistics, predictive maintenance, supply chains, and digitalization in general. Wireless sensors and wireless sensor networks (WSNs) provide, in this context, significant advantages as they are flexible and easily deployable. They have reduced installation and maintenance costs and contributed by reducing cables and preinstalled infrastructure, leading to improved reliability. WSNs can be retrofitted in machines to provide direct information from inside the processes. Recent developments have revealed exciting possibilities to enhance energy harvesting (EH) and wireless energy transmission, enabling a reliable use of wireless sensors in smart factories. This review provides an overview of the potential of energy aware WSNs for industrial applications and shows relevant techniques for realizing a sustainable energy supply based on energy harvesting and energy transfer. The focus is on high-performance converter solutions and improvement of frequency, bandwidth, hybridization of the converters, and the newest trends towards flexible converters. We report on possibilities to reduce the energy consumption in wireless communication on the node level and on the network level, enabling boosting network efficiency and operability. Based on the existing technologies, energy aware WSNs can nowadays be realized for many applications in smart factories. It can be expected that they will play a great role in the future as an enabler for digitalization in this decisive economic sector.
... They demonstrate the feasibility of implementing a WuR with commercially available off-chip components by demonstrating a radio frequency envelope detection (RFED) WuR on a PCB mount. The most significant power consumption savings are observed when WuRs are used in low-traffic and low-density WSNs, mainly because the main transceiver is in the sleep mode for most of the time [11]. However, this type of customized platform is not cost-effective. ...
... Equation (10) shows the energy saving for the case where P k (T k ) = P s4 − P k in Equation (9) and subtracting the additional power consumption E TR . Equation (11) shows the amount of power saving. ...
Wireless sensor nodes are heavily resource-constrained due to their edge form factor, which has motivated increasing battery life through low-power techniques. This paper proposes a power management method that leads to less energy consumption in an idle state than conventional power management systems used in wireless sensor nodes. We analyze and benchmark the power consumption between Sleep, Idle, and Run modes. To reduce sensor node power consumption, we develop fine-grained power modes (FGPM) with five states which modulate energy consumption according to the sensor node's communication status. We evaluate the proposed method on a test bench Mica2. As a result, the power consumed is 74.2% lower than that of conventional approaches. The proposed method targets the reduction of power consumption in IoT sensor modules with long sleep mode or short packet data in which most networks operate.
... To minimize energy consumption modern receivers are typically duty cycled [1]- [7], i.e., they listen only at predetermined time periods. To alert the receiver of an incoming message, the transmitter sends a preamble either at the beginning of a listening period (e.g., [1]- [3], [8]), or immediately in which case the preamble is long enough to cover at least one listening period (e.g., [6], [9]). In both cases the receiver performs a binary hypothesis test during the listening periods to decide whether or not a preamble is present. ...
... Indeed, as suggested in Section IV, the implementation overhead of AdaSense with respect to a non-adaptive receiver appears to be negligible. This suggests that duty cycled receivers, including the duty-cycled wake-up receivers [8], [9], [17], [29], could benefit from AdaSense. ...
... where (14) follows from the fact that the BMAC detection rule declares M = 1 if and only if Y i > η for i ∈ {1, . . . , n} and where (15) follows from (9). Similarly, we have ...
Channel sensing consists of probing the channel from time to time to check whether or not it is active - say, because of an incoming message. When communication is sparse with information being sent once in a long while, channel sensing becomes a significant source of energy consumption. How to reliably detect messages while minimizing the receiver energy consumption? This paper addresses this problem through a reconfigurable scheme, referred to as AdaSense, which exploits the dependency between the receiver noise figure (i.e., the receiver added noise) and the receiver power consumption; a higher power typically translates into less noisy channel observations. AdaSense begins in a low power low reliability mode and makes a first tentative decision based on a few channel observations. If a message is declared, it switches to a high power high reliability mode to confirm the decision, else it sleeps for the entire duration of the second phase. Compared to prominent detection schemes such as the BMAC protocol, AdaSense provides relative energy gains that grow unbounded in the small probability of false-alarm regime, as communication gets sparser. In the non-asymptotic regime energy gains are 30% to 75% for communication scenarios typically found in the context of wake-up receivers.
